Mazenet offers mobile data training by conducting coding instruction on iOS and Android. Sencha Touch mobile web App development UI Framework provides the developer with the required web apps with data for touch-friendly mobiles.

Big Data Hadoop

The collection of open-source software utilities that could solve problems involving massive data and computation.It provides a software framework for distributed storage and processing of big data using the MapReduce programming model. Source - Wiki

Apache Spark and Scala

Scala is named for its scalability on JVM and so it is used for writing Apache Spark. For working on Spark projects, Big Data developers use Scala as the most prominent language. Syntax is much simpler when compared to Java and C++

Hadoop Administration Python Spark using PySpark

A collaboration of Apache spark and python, which helps data scientists interface with Resilient Distributed Datasets in apache spark and python. For any big data processing we would need a framework as Hadoop to process data efficiently.

Splunk Power User & Admin

"Understand Splunk Power User/ Admin concepts Apply various Splunk techniques to visualize data using different graphs and dashboards Implement Splunk in the organization to Analyze and Monitor systems for operational intelligence Configure alerts and reports for monitoring purposes Troubleshoot different application logs issues using SPL (Search Processing Language) Implement Splunk Indexers, Search Heads, Forwarder, Deployment Servers & Deployers

Apache Kafka

It is written in Scala and Java, Which is an open-source stream-processing software platform.It helps to handle data pipeline for high speed filtering and pattern matching on the fly.

Apache Solr

A search platform written in Java, It is highly reliable, scalable and fault tolerant. It’s major features are full-text search, real-time indexing and dynamic clustering.

ELK Stack

ELK Stack consists of Elasticsearch, Logsearch and Kibana, each is an individual project. It is well built to work together and will work exceptionally.

Comprehensive Hive

Comprehensive Hive training will help you to understand concepts like Loading, Querying and Importing data in Hive.

MapReduce Design

Building effective algorithms and analytics for Hadoop and other systems. It helps in processing data that is scattered over hundreds of computer.It is recently popularized by Google and Hadoop.

Apache Storm

A open-source distributed real-time computational system, which is free and capable of processing streaming data at an unprecedented speed.

Comprehensive Pig

In this module, you will learn the basics of Pig, types of use cases where Pig van be used, tight coupling between Pig and Mapreduce, and Pig Latin scripting.

Mastering Apache Ambari

The main objective of Apache Ambari is to make the management of Hadoop easier for developers and administrators. By mastering Apache Ambari, one can become Hadoop Administrator.

Comprehensive Hbase

It runs on top of HDFS (Hadoop Distributed File System) to provide Google’s Bigtable essentials to Hadoop. It is an open-source, non-relational, distributed database model.

Comprehensive MapReduce

This Framework will allow us to perform distributed and parallel processing on large data set. This training will help you to solve use cases. Companies as Facebook, Twitter uses MapReduce.